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RESEARCH PAPER · Materials Today Physics · 2020

Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learning

I. Ohkubo, Zhufeng Hou, Jiyeon N. Lee, T. Aizawa, Mikk Lippmaa, Toyohiro Chikyow, Koji Tsuda, Takao Mori

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Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learningOriginalExperimental design for the highly accurate prediction of material properties using descriptors obtained by measurement9Black-Box Optimization for Automated Discovery138Electronic and lattice properties of nanostructured TiN/MgO and ScN/MgO superlattices1Control of Competing Thermodynamics and Kinetics in Vapor Phase Thin-Film Growth of Nitrides and Borides12Physics-Based Feature Makes Machine Learning Cognizing Crystal Properties Simple4Enhanced Conductivity and Microstructure in Highly Textured TiN1–x/c-Al2O3 Thin Films7Learning time-dependent deposition protocols to design thin films via genetic algorithms10Application of machine learning to reflection high-energy electron diffraction images for automated structural phase mapping31Artificial intelligence methods for applied superconductivity: material, design, manufacturing, testing, operation, and condition monitoring83Nanoarchitectonics: the role of artificial intelligence in the design and application of nanoarchitectures44Prediction of operating dynamics in floating-zone crystal growth using Gaussian mixture model1Process-Informatics-Assisted Preparation of Lithium Titanate Crystals with Various Sizes and Morphologies5Application of Information Science and Technology to GaN Crystal Growth0Cuprate superconducting materials above liquid nitrogen temperature from machine learning6Design of antimicrobial peptides containing non-proteinogenic amino acids using multi-objective Bayesian optimisation24Relationships between synthesis conditions and TiN coating properties discovered from the data driven approach16Data-driven optimization of FePt heat-assisted magnetic recording media accelerated by deep learning TEM image segmentation20Methods, progresses, and opportunities of materials informatics72Autonomous sputter synthesis of thin film nitrides with composition controlled by Bayesian optimization of optical plasma emission26Optical properties of plasmonic titanium nitride thin films from ultraviolet to mid-infrared wavelengths deposited by pulsed-DC sputtering, thermal and plasma-enhanced atomic layer deposition383D printing in materials manufacturing industry: A realm of Industry 4.055Optimization of Core–Shell Nanoparticles Using a Combination of Machine Learning and Ising Machine7Accelerating the combinatorial optimization process for phosphor materials by Bayesian optimization6Microstructure evolution under thermo-mechanical operating of rocksalt-structure TiN via neural network potential7Formation and Prediction of Tribotechnical Properties of Ion-Plasma Diamond-Like Coatings under Stabilization with Nitrogen0NITROGEN-STABILIZED DLC COATINGS: OPTIMIZATION OF PROPERTIES AND DEPOSITION PARAMETERS USING RANDOMIZED TREE AND NEURAL NETWORK ALGORITHMS3Formation and Prediction of the Properties of Ion-Plasma Diamond-Like Coatings under Nitrogen Stabilization5Atomic layer epitaxy of twinned TiN by hydrogen-manipulated tailoring on monolayer9Performance metrics to unleash the power of self-driving labs in chemistry and materials science93Bayesian optimization-driven enhancement of the thermoelectric properties of polycrystalline III-V semiconductor thin films20Bayesian optimization for stable properties amid processing fluctuations in sputter deposition14Predictive Modeling of Vickers Hardness Using Machine Learning Techniques on D2 Steel with Various Treatments18Designing semiconductor materials and devices in the post-Moore era by tackling computational challenges with data-driven strategies33Quantum and classical machine learning investigation of synthesis–structure relationships in epitaxially grown wide band gap semiconductors4Nitrogen-Stabilized DLC Coatings: Optimization of Properties and Deposition Parameters Using Randomized Tree and Neural Network Algorithms6Data-driven investigation of thickness variations in multilayer thin film coatings3Bayesian Optimization for Controlled Chemical Vapor Deposition Growth of WS213High-quality multilayer graphene on insulators via metal catalyst alloying in layer exchange with Bayesian optimization0Machine learning for metal additive manufacturing process optimization4Epitaxy of Emerging Materials and Advanced Heterostructures for Microelectronics and Quantum Sciences12Zinc Stabilized Cation Ordered Chalcopyrite Thin Film for Enhanced Thermoelectric Power Generation Near Room Temperature2Multimodal Machine Learning Analysis of GaSe Molecular Beam Epitaxy Growth Conditions8Integrated process-property modeling of YBa2Cu3O7 superconducting film for data and model driven process design6Active learning-enhanced yttrium oxyhydride thin films for photoinduced insulator-to-metal transitions1Rapid analysis of point-contact Andreev reflection spectra via machine learning with physics-guided data augmentation1Machine Learning-Driven Design and Optimization of Multi-Metal Nitride Hard Coatings via Multi-Arc Ion Plating Using Genetic Algorithm and Support Vector Regression4Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab14High-throughput materials exploration system for the anomalous Hall effect using combinatorial experiments and machine learning3Modeling strategies for hydrogen reduction of high-purity metals: From DFT to ReaxFF and machine learning0A self-driving physical vapor deposition system making sample-specific decisions on the fly14Autonomous closed-loop exploration of composition-spread films for the anomalous Hall effect11Overcoming surface energy to control Cu3N epitaxial growth0Long photocarrier lifetimes in CsPbBr 3 films deposited by a machine-learning-assisted IR-laser molecular beam epitaxy process1Machine learning exploration of YBCO thin film growth parameters under small data constraint0Machine Learning Strategies to Circumvent Variabilities in Chemical Vapour‐Deposited Graphene Coatings for Remarkable Corrosion Resistance of Metals3Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes2Interpretable Machine Learning Uncovers the Dominance of Oxygen Partial Pressure and Crystallinity in Mo-Doped In 2 O 3 Thin Film Growth1Independent control of the thermoelectric parameters in titanium nitride thin films via crystal preferred orientation control using the combinatorial sputter coating0From Data to Discovery: Challenges and Solutions in AI-Driven Materials Science0Multi-factor Optimization of Ti/TiN/TaN and Zr-Based Nano-coatings on Ti6Al4V Substrates Using Deep Graph Learning0Tuning superconductivity in high entropy nitrides0Machine learning-driven analysis and process optimization of FePt-BN granular films for HAMR applications1

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